Transaction
ID: 45c81f2199...53d6
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
1,504.93 ERG
Tokens:
Loading assets...
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
222,811.48
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1,504.92 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 980,190
Total coins transferred: 1,504.93 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000208 ERG
Raw Transaction Data
{
"id": "45c81f2199abcdf4796d260be3c81bbed87bd18f67af824d81bb190904fa53d6",
"blockId": "76ff1e9dcaf4334335873a2722714345b38a3f46e5b1f3e652b810df4fc972d2",
"inclusionHeight": 781241,
"timestamp": 1656387923970,
"index": 10,
"globalIndex": 3446672,
"numConfirmations": 980190,
"inputs": [
{
"boxId": "59dd14c2ad96d3b19deb6c0932426513f61f48846e525a89d4eb052e9a582189",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "c54b1a99669c6d26a008d5ab4a74a7df1dfb6a8f72bc85673233618b68dfb1da",
"outputTransactionId": "62aec56c48df427d7c6a6e0433865a454289197746c5cb0b178bf12e928ce517",
"outputIndex": 0,
"outputGlobalIndex": 18446469,
"outputCreatedAt": 781225,
"outputSettledAt": 781228,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(0,-79,-30,54,-74,11,-107,-62,-58,-8,0,122,-99,-119,-68,70,15,-55,-25,-113,-104,-80,-97,-82,-55,68,-112,7,-76,11,-52,-13)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(-125,-99,-99,98,-20,-69,127,-52,-53,-107,-78,-28,5,-24,-39,-73,-99,-74,74,-70,30,72,67,-69,-78,-47,-22,3,45,-72,38,-98)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(7,-88,100,-115,13,-32,-9,-56,122,-83,65,-95,-5,-58,-45,-109,-90,-83,-107,88,77,56,-60,124,-120,18,91,-17,16,28,41,-23)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(-88,-42,51,-34,-25,5,-1,-112,-29,24,16,19,56,20,85,53,61,-84,45,-111,54,105,82,32,-102,-58,-77,-7,-51,-52,35,-23)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.tokens\n val tuple6 = coll5(placeholder[Int](2))\n val coll7 = tuple6._1\n val bool8 = coll4 == coll7\n val box9 = OUTPUTS(placeholder[Int](3))\n val coll10 = box9.R4[Coll[Long]].get\n val coll11 = SELF.R4[Coll[Long]].get\n val l12 = tuple6._2\n val coll13 = box9.tokens\n val tuple14 = coll13(placeholder[Int](4))\n val l15 = tuple14._2\n val l16 = CONTEXT.preHeader.timestamp\n val l17 = tuple3._2\n val coll18 = placeholder[Coll[Byte]](5)\n val tuple19 = coll13(placeholder[Int](6))\n val tuple20 = coll5(placeholder[Int](7))\n val l21 = coll11(placeholder[Int](8))\n val bool22 = allOf(\n Coll[Boolean](\n box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n placeholder[Int](9)\n ) == l21, coll13.size == placeholder[Int](10)\n )\n )\n if (bool8) {(\n val tuple23 = coll2(placeholder[Int](11))\n val l24 = tuple23._2\n val l25 = coll11(placeholder[Int](12))\n val coll26 = box1.R4[Coll[Long]].get\n val coll27 = box1.R5[Coll[Byte]].get\n val box28 = OUTPUTS(placeholder[Int](13))\n val tuple29 = box28.tokens(placeholder[Int](14))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n placeholder[Int](18)\n ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n Long\n ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n placeholder[Int](26)\n ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n 29\n ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n )\n )\n )\n )} else {(\n val box23 = INPUTS(placeholder[Int](32))\n val coll24 = box23.tokens\n val tuple25 = coll24(placeholder[Int](33))\n val coll26 = tuple25._1\n if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n val box27 = INPUTS(placeholder[Int](36))\n val coll28 = box27.R4[Coll[Long]].get\n val l29 = coll11(placeholder[Int](37))\n val l30 = coll10(placeholder[Int](38))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n placeholder[Int](43)\n ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n placeholder[Int](48)\n ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n )\n )\n )\n )} else {(\n val l27 = coll11(placeholder[Int](50))\n val l28 = coll10(placeholder[Int](51))\n if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n val coll33 = tuple31._2.tokens\n val l34 = tuple31._1\n if (coll33.size == placeholder[Int](54)) { l34 } else {(\n val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n val i36 = coll35.size\n if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n )}\n }) }\n val l30 = func29(INPUTS)\n val l31 = func29(OUTPUTS)\n val coll32 = box23.R4[Coll[Long]].get\n val l33 = coll32(placeholder[Int](59))\n val l34 = l16 - l33 / placeholder[Int](60).toLong\n val l35 = l27 - l28\n val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n l35 * placeholder[Long](72) / placeholder[Long](73)\n }\n }\n }\n }\n val box37 = INPUTS(placeholder[Int](74))\n val l38 = coll32(placeholder[Int](75))\n val l39 = coll11(placeholder[Int](76))\n val tuple40 = coll24(placeholder[Int](77))\n val l41 = tuple40._2 - l35\n val bool42 = l41 == placeholder[Long](78)\n val coll43 = tuple40._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n placeholder[Long](84)\n } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n placeholder[Long](88)\n } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n 90\n )) {(\n val box44 = OUTPUTS(placeholder[Int](91))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](92))\n val tuple47 = coll45(placeholder[Int](93))\n val coll48 = box44.R4[Coll[Long]].get\n allOf(\n Coll[Boolean](\n box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n Long\n ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n )\n )\n )} else { placeholder[Boolean](97) }\n )\n )\n )\n )} else { sigmaProp(placeholder[Boolean](98)) }\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "f419099a27aaa5f6f7d109d8773b1862e8d1857b44aa7d86395940d41eb53806",
"index": 0,
"amount": 1,
"name": "EGIO Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1431964fa6559e969a7bf047405d3f63f7592354d432556f79894a12c4286e81",
"index": 1,
"amount": 999999904,
"name": "EGIO Stake Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1105c48391d9b60902c00180dc9097b36080f0b252",
"sigmaType": "Coll[SLong]",
"renderedValue": "[161960042722,1,96,1656136800000,86400000]"
}
}
},
{
"boxId": "2f7c6eaba03afa60aae6687cc398f3c348fcde10b3738b9e0e1a181f49b1c6f2",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "5ac1fbb24e98b6e845e7d6c04ed3be957280e0a752816241030d7ff0c7ed5db7",
"outputTransactionId": "5ba6f4c6f07b4caff60f28a6d2f4f126ebac22eac4e9adaa064bbf0fae72cabe",
"outputIndex": 1,
"outputGlobalIndex": 18341770,
"outputCreatedAt": 779213,
"outputSettledAt": 779217,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-88,-42,51,-34,-25,5,-1,-112,-29,24,16,19,56,20,85,53,61,-84,45,-111,54,105,82,32,-102,-58,-77,-7,-51,-52,35,-23)\n3: 1\n4: 0\n5: 0\n6: 1\n7: 1\n8: 0\n9: 0\n10: 1\n11: 1\n12: 1\n13: 3\n14: 0\n15: 1\n16: 2\n17: Coll(-12,25,9,-102,39,-86,-91,-10,-9,-47,9,-40,119,59,24,98,-24,-47,-123,123,68,-86,125,-122,57,89,64,-44,30,-75,56,6)\n18: 1\n19: 1\n20: false\n21: true\n22: false",
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"assets": [
{
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"type": "EIP-004"
},
{
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}
],
"additionalRegisters": {
"R4": {
"serializedValue": "110202e2cca09fb360",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1,1656145318705]"
},
"R5": {
"serializedValue": "0e2044179632019e345139ed6e9758df6fd923812b877327fa9a1b09e476d27b2b9b",
"sigmaType": "Coll[SByte]",
"renderedValue": "44179632019e345139ed6e9758df6fd923812b877327fa9a1b09e476d27b2b9b"
}
}
},
{
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"outputTransactionId": "2d6c3817f4f095c280abbdc557ab824d4363ddb735451735caacbc6bd4eb538e",
"outputIndex": 2,
"outputGlobalIndex": 18446490,
"outputCreatedAt": 781227,
"outputSettledAt": 781229,
"ergoTree": "0008cd03c3ce4fd9a252ec9e58a766481f7d09dae2c9c2c48f22b47d97c4af12347a2ffc",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(c3ce4f,97456a,...)))}",
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"type": "EIP-004"
},
{
"tokenId": "b33b5f320ea5691ad6a5de682ca7253bb7cc346421df5d8b872427afc15055a4",
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"type": "EIP-004"
},
{
"tokenId": "87fb172d186d260f1855eb627fc7a70beb9bafdcadfd5c1ff392f094442cf35e",
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"name": "Paideia Staker Round whitelist token",
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},
{
"tokenId": "0cd8c9f416e5b1ca9f986a7f10a84191dfb85941619e49e53c0dc30ebf83324b",
"index": 58,
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"name": "COMET",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "438fb5dca3a4390cfd6b170a91420f45e56db43d827858558c82b6dfa1d7bf1a",
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"name": "Paideia Seed Round Vesting Key",
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"type": "EIP-004"
},
{
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},
{
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"name": "Ergnome #796 Cryptoapollo the Portfolio Protector",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "d6bffad43b233e7c8be47cc7ecffb7b6b702ef57fca9a0d28907cf9dc46ebc72",
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"amount": 1,
"name": "$COMET Beggar Yellow",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "472d9adfdc87fc441a8bdb72261e4b58a31e4761c4e67e26dbc3b34b1d1098f4",
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"name": "Ergnome #274 Matsu, the Chill Procrastinator",
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"type": "EIP-004"
},
{
"tokenId": "ff04ab0083d9a3b168c7959d878cb2e27ee65c89e318974d0102baeafded284b",
"index": 64,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "bbbbcb631f818166b5844953026aa3de0ab280170f4c8b1296f476601e5141d3",
"index": 65,
"amount": 1,
"name": "Paideia Staker Round Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "02f31739e2e4937bb9afb552943753d1e3e9cdd1a5e5661949cb0cef93f907ea",
"index": 66,
"amount": 20000000,
"name": "Terahertz",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "708b05e0bca293b96fba2bf29ae7869201bddfbcde26cbf4c63e42d694905164",
"index": 67,
"amount": 1,
"name": "ergopad Stake Key",
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"type": "EIP-004"
},
{
"tokenId": "6ba81d982c87c5c187286e81468517a0a758257a4aacf922f15bf2510069f28f",
"index": 68,
"amount": 1,
"name": "swampaudio seed Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fbbaac7337d051c10fc3da0ccb864f4d32d40027551e1c3ea3ce361f39b91e40",
"index": 69,
"amount": 53824,
"name": "kushti",
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"type": "EIP-004"
},
{
"tokenId": "28c781ae40529e846d811acfb7170af0a25bb2cdc4e904d1efd6699d082b1844",
"index": 70,
"amount": 1,
"name": "[SigmaWorlds] Earth Worlds: uranus",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f89a9249d7768eb25569579ccd659fe2807a8e3775601c58ed4e87a1b2fc691d",
"index": 71,
"amount": 1,
"name": "Halloween 2021 #0008",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "6f96c0e88bc07f3ae6780437a55747ace88aee620cc1292f69512ffd2525f32b",
"index": 72,
"amount": 1,
"name": "Gnomekin #2507 ERGnomes Halloween '21 Special",
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"type": "EIP-004"
},
{
"tokenId": "27a7f3eb834658b532a0bb42217c128e1ba8426d605ec253aafaae6fbb5771ca",
"index": 73,
"amount": 1,
"name": "ERGnomes Loyalty Crypto vs Fiat [198/221]",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1414065795f6aba405f029b7871c6b54f029e3ca3d88ad310d38c9af6e3bee1d",
"index": 74,
"amount": 1,
"name": "Ergnome #1007 \"Dr. Pad the Gnomengineer\"",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "669e24e2b39b06b6134bc0dd67ee57f4ce2cbc1a5b552e39d655737a05f6f384",
"index": 75,
"amount": 2,
"name": "Have_A_Nice_Day",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ebb7158e2ee67e2f8e4b6be76b13adc97b11d99b7ebccc5058042fa270919e32",
"index": 76,
"amount": 1,
"name": "Ergnome #1372 \"Machimasu the Raffle Grandpa\"",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f0c958edb3a3354f2494289ddf4a143f81d95c343f257f067f26cc73454309fc",
"index": 77,
"amount": 1,
"name": "Ergnome #293 Matsu, the Chill Procrastinator",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "47cea60dadb2984e55dff5be54679bbf741d2f26298018bf0a5b0d6fdc185f39",
"index": 78,
"amount": 1,
"name": "Bananart #0029",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0456ab5900c96c06cb57f13f4d9d79c53912a6fb8ba698964a41e3b6b44c9be1",
"index": 79,
"amount": 1,
"name": "#1",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ccd4e12aeee3c5c758e55c2ee1f900628d7634ed4cfc73f830381b5e60e4ecd0",
"index": 80,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "82a80d253116c64a31c27aa8d77939818b784ede0a48aa953ccfac74e16a21d3",
"index": 81,
"amount": 1,
"name": "Halloween 2021 #0049",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8c96664efde79f5cd71577612d036c35f4a4f6df01353bcd412612f1cd410805",
"index": 82,
"amount": 1,
"name": "Ergnome #759 Lichnyy the BPSAA Privacyshroom",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "e4f52666f577adedba70c80556d608773ef0b9e0041a877b33c8cddd1f72dcda",
"transactionId": "45c81f2199abcdf4796d260be3c81bbed87bd18f67af824d81bb190904fa53d6",
"blockId": "76ff1e9dcaf4334335873a2722714345b38a3f46e5b1f3e652b810df4fc972d2",
"value": 1000000,
"index": 0,
"globalIndex": 18446875,
"creationHeight": 781239,
"settlementHeight": 781241,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(0,-79,-30,54,-74,11,-107,-62,-58,-8,0,122,-99,-119,-68,70,15,-55,-25,-113,-104,-80,-97,-82,-55,68,-112,7,-76,11,-52,-13)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(-125,-99,-99,98,-20,-69,127,-52,-53,-107,-78,-28,5,-24,-39,-73,-99,-74,74,-70,30,72,67,-69,-78,-47,-22,3,45,-72,38,-98)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(7,-88,100,-115,13,-32,-9,-56,122,-83,65,-95,-5,-58,-45,-109,-90,-83,-107,88,77,56,-60,124,-120,18,91,-17,16,28,41,-23)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(-88,-42,51,-34,-25,5,-1,-112,-29,24,16,19,56,20,85,53,61,-84,45,-111,54,105,82,32,-102,-58,-77,-7,-51,-52,35,-23)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.tokens\n val tuple6 = coll5(placeholder[Int](2))\n val coll7 = tuple6._1\n val bool8 = coll4 == coll7\n val box9 = OUTPUTS(placeholder[Int](3))\n val coll10 = box9.R4[Coll[Long]].get\n val coll11 = SELF.R4[Coll[Long]].get\n val l12 = tuple6._2\n val coll13 = box9.tokens\n val tuple14 = coll13(placeholder[Int](4))\n val l15 = tuple14._2\n val l16 = CONTEXT.preHeader.timestamp\n val l17 = tuple3._2\n val coll18 = placeholder[Coll[Byte]](5)\n val tuple19 = coll13(placeholder[Int](6))\n val tuple20 = coll5(placeholder[Int](7))\n val l21 = coll11(placeholder[Int](8))\n val bool22 = allOf(\n Coll[Boolean](\n box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n placeholder[Int](9)\n ) == l21, coll13.size == placeholder[Int](10)\n )\n )\n if (bool8) {(\n val tuple23 = coll2(placeholder[Int](11))\n val l24 = tuple23._2\n val l25 = coll11(placeholder[Int](12))\n val coll26 = box1.R4[Coll[Long]].get\n val coll27 = box1.R5[Coll[Byte]].get\n val box28 = OUTPUTS(placeholder[Int](13))\n val tuple29 = box28.tokens(placeholder[Int](14))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n placeholder[Int](18)\n ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n Long\n ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n placeholder[Int](26)\n ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n 29\n ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n )\n )\n )\n )} else {(\n val box23 = INPUTS(placeholder[Int](32))\n val coll24 = box23.tokens\n val tuple25 = coll24(placeholder[Int](33))\n val coll26 = tuple25._1\n if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n val box27 = INPUTS(placeholder[Int](36))\n val coll28 = box27.R4[Coll[Long]].get\n val l29 = coll11(placeholder[Int](37))\n val l30 = coll10(placeholder[Int](38))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n placeholder[Int](43)\n ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n placeholder[Int](48)\n ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n )\n )\n )\n )} else {(\n val l27 = coll11(placeholder[Int](50))\n val l28 = coll10(placeholder[Int](51))\n if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n val coll33 = tuple31._2.tokens\n val l34 = tuple31._1\n if (coll33.size == placeholder[Int](54)) { l34 } else {(\n val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n val i36 = coll35.size\n if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n )}\n }) }\n val l30 = func29(INPUTS)\n val l31 = func29(OUTPUTS)\n val coll32 = box23.R4[Coll[Long]].get\n val l33 = coll32(placeholder[Int](59))\n val l34 = l16 - l33 / placeholder[Int](60).toLong\n val l35 = l27 - l28\n val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n l35 * placeholder[Long](72) / placeholder[Long](73)\n }\n }\n }\n }\n val box37 = INPUTS(placeholder[Int](74))\n val l38 = coll32(placeholder[Int](75))\n val l39 = coll11(placeholder[Int](76))\n val tuple40 = coll24(placeholder[Int](77))\n val l41 = tuple40._2 - l35\n val bool42 = l41 == placeholder[Long](78)\n val coll43 = tuple40._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n placeholder[Long](84)\n } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n placeholder[Long](88)\n } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n 90\n )) {(\n val box44 = OUTPUTS(placeholder[Int](91))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](92))\n val tuple47 = coll45(placeholder[Int](93))\n val coll48 = box44.R4[Coll[Long]].get\n allOf(\n Coll[Boolean](\n box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n Long\n ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n )\n )\n )} else { placeholder[Boolean](97) }\n )\n )\n )\n )} else { sigmaProp(placeholder[Boolean](98)) }\n )}\n )}\n}",
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},
{
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}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[158989223050,1,95,1656136800000,86400000]"
}
},
"spentTransactionId": "c8c47795a27605e685f8c378bcdc5696341f93c805a487a5bc4c322dc11f4915",
"mainChain": true
},
{
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"ergoTree": "0008cd03c3ce4fd9a252ec9e58a766481f7d09dae2c9c2c48f22b47d97c4af12347a2ffc",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(c3ce4f,97456a,...)))}",
"address": "9hx3HoWVZ9ErUWmFAFi7XYTie6uUMWWwULuGVFdJFqNNf9CdRcB",
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{
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}
],
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{
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"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
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{
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